Speech Emotion Recognition Based on Voice Fundamental Frequency

Teodora Dimitrova-Grekow , Aneta Klis , Magdalena Igras-Cybulska

Abstract

The human voice is one of the basic means of communication, thanks to which one also can easily convey the emotional state. This paper presents experiments on emotion recognition in human speech based on the fundamental frequency. AGH Emotional Speech Corpus was used. This database consists of audio samples of seven emotions acted by 12 different speakers (6 female and 6 male). We explored phrases of all the emotions – all together and in various combinations. Fast Fourier Transformation and magnitude spectrum analysis were applied to extract the fundamental tone out of the speech audio samples. After extraction of several statistical features of the fundamental frequency, we studied if they carry information on the emotional state of the speaker applying different AI methods. Analysis of the outcome data was conducted with classifiers: K-Nearest Neighbours with local induction, Random Forest, Bagging, JRip, and Random Subspace Method from algorithms collection for data mining WEKA. The results prove that the fundamental frequency is a prospective choice for further experiments.
Author Teodora Dimitrova-Grekow (FCS / DDMCG)
Teodora Dimitrova-Grekow,,
- Department of Digital Media and Computer Graphics
, Aneta Klis
Aneta Klis,,
-
, Magdalena Igras-Cybulska
Magdalena Igras-Cybulska,,
-
Journal seriesArchives of Acoustics, ISSN 0137-5075, e-ISSN 2300-262X, (N/A 70 pkt)
Issue year2019
Vol44
No2
Pages277-286
Publication size in sheets0.5
Keywords in Englishemotion recognition; speech signal analysis; voice analysis; fundamental frequency; speech corpora
ASJC Classification3102 Acoustics and Ultrasonics
DOIDOI:10.24425/aoa.2019.128491
URL http://acoustics.ippt.gov.pl/index.php/aa/article/view/2338
Internal identifier000045537
Languageen angielski
LicenseJournal (articles only); published final; Other open licence; with publication
Score (nominal)70
Score sourcejournalList
ScoreMinisterial score = 70.0, 30-03-2020, ArticleFromJournal
Publication indicators Scopus SNIP (Source Normalised Impact per Paper): 2018 = 0.755; WoS Impact Factor: 2018 = 0.899 (2) - 2018=0.893 (5)
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